Precision
A performance metric calculated as the ratio of correct positive predictions to all positive predictions made by a model, measuring the reliability of the model's positive classifications.
In plain language
Of all the things the AI flagged as positive, how many were actually correct? If a fraud detection system flags 1,000 transactions as suspicious and 950 truly are fraudulent, its precision is 95%.
Why this matters
Precision matters for governance because high false positive rates can harm legitimate users or waste investigation resources. Your AI deployment framework should define acceptable precision thresholds for each use case and monitor them continuously in production.
Relevance
ImplementationA key performance metric that governs the operational impact of false positives, requiring clear thresholds and ongoing monitoring in production.
Related terms
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